Projects with this topic
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Isolating local MCP servers from sensitive data
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a self-hosted, locally-routed LLM stack with a default-deny security posture. your models. your machine. your terms.
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A Burp Suite extension for assessing web apps built on LLM agents
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Red Team AI Benchmark: Evaluating LLMs for authorized offensive-security tasks. Red Team AI Benchmark is a CLI model-evaluation benchmark. It measures how LLMs understand and respond to red-team questions and security scenarios; it is not a tool for carrying out those activities. Version 2 uses a rubric-based dataset instead of judging answers only against one golden response.
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Kevlar Benchmark: OWASP Top 10 for Agentic Apps (AI-Agents) 2026 a Red Team Benchmark.
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Otōto is an MCP server for Claude Code and OpenCode. You can hand off LLM tasks (and other jobs!) to Ototo saving tokens and context.
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KiM Explorer is a two-stage RAG application for transport policy research publications from the KiM Netherlands Institute for Transport Policy Analysis. Users perform semantic search to identify relevant documents, manually select publications, then interact with an LLM using full document context rather than chunks. Built with Python/NiceGUI/OpenAI API, featuring citation generation, conversation history, filtering, and web/CLI interfaces. https://explorer.kim.rijkscloud.nl/
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A lrc fetcher for stream music and aonsoku music player with translation and llm support.
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A unified Python interface to select and use multiple Large Language Model (LLM) providers through a common API.
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🛒 AI chat & product/category summaries in Amazon shopping, powered by the latest LLMsUpdated -
A web AI interface using a selected number of models and trained to teach the German language.
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LLM Workflow Router is a stateless middleware engine designed to enforce explicit execution topology in AI systems that rely on large language models. It evaluates interaction metadata against strictly declared workflow rules and returns a terminal state.
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💬 Epic prompts to turbo-charge your LLM chatbots.Updated -
Model Verification Layer is a modular system for evaluating, comparing, and validating the behavior of large language models using structured benchmarks, logic consistency checks, cross-model consensus analysis, and policy-aware constraints. It provides a transparent framework for understanding how different AI models perform under identical conditions, enabling more reliable model selection, safer deployment, and user-adaptive decision making. https://roxanneardary.com/model-verification-layer/
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SynapCache is a distributed, zero-memory-loss caching system for all LLM outputs, designed to be LLM-agnostic, high-performance, and scalable. It combines TurboQuant-style compression, semantic search, edge caching, and predictive intelligence to store and retrieve outputs efficiently, ensuring instant recall and minimal resource usage. With developer-friendly SDKs, plugin support, and multi-cloud deployment, SynapCache provides a universal neural memory layer for modern AI workflows. https://roxanneardary.com/synapcache/
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